Artificial intelligence used by UK police to predict crimes amplifies human bias

Artificial intelligence technology used by police forces in the UK to predict future crimes replicates - and in some cases amplifies - human prejudices, according to a new report. While "predictive policing" tools have been used in the UK since at least 2004, advances in machine learning and AI have enabled the development of more sophisticated systems. These are now used for a wide range of functions including facial recognition and video analysis, mobile phone data extraction, social media intelligence analysis, predictive crime mapping and individual risk assessment. However, the report by the Royal United Services Institute (RUSI) warns that human biases are being built into these machine learning algorithms, resulting in people being unfairly discriminated against due to their race, sexuality and age. One police officer who was interviewed for the report commented that: "Young black men are more likely to be stop and searched than young white men, and that's purely down to human bias. "That human bias is then introduced into the datasets, and bias is then generated in the outcomes of the application of those datasets." In addition to these inherent biases, the report points out that individuals from disadvantaged sociodemographic backgrounds are likely to engage with public services more frequently. As a result, police often have access to more data relating to these individuals, which "may in turn lead to them being calculated as posing a greater risk". Matters could worsen over time, another officer said, when software is used to predict future crime hotspots. "We pile loads of resources into a certain area and it becomes a self-fulfilling prophecy, purely because there's more policing going into that area, not necessarily because of discrimination on the part of officers," the officer said. The report also warns that police forces could become over-reliant on the AI to predict future crimes, and discount other relevant information. "Officers often disagree with the algorithm.